Firstly, loading package and data

Loading Package…

library(dppbar)
## Warning in as.POSIXlt.POSIXct(Sys.time()): unknown timezone 'zone/tz/2019b.
## 1.0/zoneinfo/Asia/Shanghai'

Loading Dataset…

To fully illustrate the usage of package to accomplish this task, we use two datasets of different structure. They are “Chinese Real Estate Industry Companies’ Financial Charts(2007-2016)” and “Some Macroeconomic Data of China(2008-2016)”. Head lines of each dataset is shown below.

Chinese Real Estate Industry Companies’ Financial Charts(2007-2016)

##   Year  证券代码 证券简称 season  roa
## 1 2007 000002.SZ    万科A      2 8.18
## 2 2008 000002.SZ    万科A      2 6.66
## 3 2009 000002.SZ    万科A      2 7.37
## 4 2010 000002.SZ    万科A      2 8.86
## 5 2011 000002.SZ    万科A      2 8.09

Some Macroeconomic Data of China(2008-2016)

##   year     ROE   CPI   PPI      GDP
## 1 2008 -0.4826 105.9 106.9 319515.5
## 2 2009  0.2078  99.3  94.6 349081.4
## 3 2010  0.2028 103.3 105.5 413030.3
## 4 2011  0.3533 105.4 106.0 489300.6
## 5 2012  0.2597 102.6  98.3 540367.4

Secondly, done the plot within five lines of R code:

bar_plot(dataframe=estate_fin_charts,ctg.idx = 'Year',num.idx = 'income',
         condition.idx = '证券简称',criteria=2016,top_N=10,
         colors=brewer.pal(12,'Set3'),xaxis_name='年份',yaxis_name='营业收入（亿元）',
         title='2016年营业收入前12名房地产企业历年营收变化',
         paper_bgcolor='#ccece6',margin=list(t=36,l=24))
bar_plot(dataframe=macro_data_chn,ctg.idx='year',num.idx=c(9:12),
         criteria = 2016,colors = brewer.pal(4,'Set1'),
         xaxis_name = '年份',yaxis_name = '商品价格（元/吨）',
         title='一些大宗商品的历年价格变化',
         paper_bgcolor='#ccece6',margin=list(t=36,l=24))